205 Progressive Damage Analysis (PDA) and Mechanism Based Failure Predictions of Composites

Paul Davidson, University of Washington
Evan Pineda, NASA Glenn RC
Anthony M. Waas, University of Washington
Jaan-Willem Simon, RWTH Aachen
From molecular dynamics to simulation of large scale structures, capability of simulation tools for composite materials has come a long way over the past decade. However, much of composite materials/structural analysis methods used in industry today are still limited to linear analysis or simplified failure analysis. The primary reason is that composite material exhibit very complex interactive failure mechanisms, which are still out of reach for methods employed thus far. Complexity is compounded by numerical issues like mesh dependency, non-linear behavior, multi-scale interactive phenomena, simplified assumptions, etc. The aim of this mini-symposium is to bring together researchers in the fields of mechanics and modeling of composite materials, structural mechanics, and progressive failure analysis methods to have an open discussion on current and future methods for progressive damage analysis (PDA) of composites.
We invite papers in the following topics in the general theme of PDA of composite materials.
• Hi-Fidelity analysis methods that reproduce physical failure mechanisms
• Lo-Fidelity analysis methods that produce “effective” failure mechanism.
• Multi-scale PDA.
• Issues with PDA. Eg; Mesh size effects, mesh alignment errors, stress calculation errors using FEM, etc.
With application to items below (not limited to):
• Composite material allowable prediction.
• Composite structure failure prediction.
• Progressive damage analysis of composite joints.
• Progressive damage analysis of textile and 3D printed composites
To provide focus, the material system in consideration will be limited to composite materials currently in use in aerospace, automotive and wind energy, namely Carbon fiber composites, glass fiber composites, aramid composites, and ceramic composites. Preference will also be given to methods validated using experimental data, however, the focus of the contribution should be on the analysis.